Digital beamforming for simultaneously mitigating weak and strong interference in a navigation system

ABSTRACT

An adaptive cascaded electronic protection processing system for global navigation satellite system (GNSS) threat mitigation is provided. The system includes a precorrelation characterization component configured to provide at least one parameter characterizing a plurality of received signals. A correlator is configured to provide a plurality of correlation results, each representing one of the plurality of received signals. A spatial weight contribution component is configured to determine an optimal set of digital beam-forming weights via an optimization process according to the at least one parameter. A postcorrelation characterization component is configured to determine at least one constraint on the optimization process according to the plurality of correlation results.

RELATED APPLICATIONS

This application claims priority from U.S. Provisional PatentApplication Ser. No. 61/576,205, filed 15 Dec. 2011, which isincorporated herein in its entirety.

TECHNICAL FIELD

This invention relates to navigation systems, and more particularly, tothe use of digital beam-forming to mitigate both weak and stronginterference in a navigation system.

BACKGROUND OF THE INVENTION

The fundamental baseband digital signal-processing component used in aglobal navigation satellite system (GNSS) receiver is known as acorrelator. It correlates digitized samples of a received GNSS signaloutput by an analog-to-digital converter (ADC) with locally generatedreplicas of the carrier and spreading code components of the signalbeing received. If the local replica is adequately aligned with thecarrier and code components of the received signal, a large correlationresult is produced. The signal can be processed according to parametersof the signal derived from the aligned local replica, thereby providingobservability of the actual received signal parameters whose power levelcan be well below that of thermal noise. Fundamentally, these receivedsignal parameters are the magnitude of the despread signal and phase ofits carrier with respect to the locally generated carrier.

SUMMARY OF THE INVENTION

In accordance with an aspect of the present invention, a cascadedelectronic protection system for a global navigation satellite system(GNSS) is provided that maintains the capabilities of traditional beamforming systems for strong interference while adding a capability tomitigate weak interference which minimizes impact on measurementfidelity. Traditional digital beam forming electronic protection systemsare historically designed to operate independently from a globalnavigation satellite system (GNSS) receiver and only address the stronginterference sources distinct from thermal noise, but are challenged todeal with the weak ones which are below the thermal noise floor such asspoofing or meaconing. The cascaded approach utilizes covarianceestimates from the digital signal samples as well as autocorrelationestimates from the correlators to calculate the optimal spatial andtemporal weights to form nulls towards undesired emitters such asinterference, jamming, spoofing, and meaconing while directing gaintoward desired GNSS satellites. Cascading allows the electronicprotection system to simultaneously mitigate weak and strong signalthreats by combining multi-stream post-correlation spatial filtering andpre-correlation temporal filtering respectively within the GNSS receiveritself.

To this end, a precorrelation characterization component is configuredto provide at least one parameter characterizing a plurality of receivedsignals. A correlator is configured to provide a plurality ofcorrelation results, each representing one of the plurality of receivedsignals. A post-correlation spatial weight computation component isconfigured to determine an optimal set of digital beam-forming weightsvia an optimization process according to the at least one parameter. Apost-correlation constraint component is configured to apply at leastone constraint on the optimization process according to the plurality ofcorrelation results

In accordance with another aspect of the present invention, a secondspace time adaptive processing system for a GNSS system is provided. Apre-correlation characterization component is configured to provide atleast one parameter characterizing a plurality of received signals. Adigital antenna electronics component is configured to downconvert thereceived signal to an intermediate frequency, digitize the intermediatefrequency signal into a stream of digital samples at an associatedsampling rate, and downconvert the stream of digital samples to abaseband digital signal. A temporal filter for each baseband digitalsignal is configured to provide a temporal cancelation of emitters tomitigate narrow-band jamming using an adaptive minimization technique. Acorrelator is configured to provide a plurality of correlation results,with each correlation result representing one of the plurality ofbaseband digital signals. A spatial weight computation component isconfigured to determine an optimal set of digital beam-forming weightsvia an optimization process according to the at least one parameter tomitigate wideband jamming and weak signal threats. A post-correlationconstraint component is configured to determine at least one constrainton one of several existing optimization techniques according to theplurality of correlation results.

In accordance with yet another aspect of the invention, a method isprovided for adaptive processing in a navigation system. Temporalfiltering is applied to each of a plurality of input streams to providea plurality of filtered input streams which each mitigate temporallycorrelated interference. A covariance matrix representing the pluralityof filtered input streams is generated. A plurality of correlationresults is generated, each representing one of the plurality of filteredinput streams. A beam-forming weight is calculated for each input streamfrom the covariance matrix and the plurality of correlation results tomitigate spatially correlated interference.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a cascaded Electronic Protection (EP) assembly for aglobal navigation satellite system (GNSS) in accordance with an aspectof the present invention.

FIG. 2 illustrates one implementation of a global navigation satellitesystem (GNSS) receiver in accordance with an aspect of the presentinvention.

FIG. 3 illustrates a method for adaptive processing in a navigationsystem in accordance with an aspect of the present invention.

DETAILED DESCRIPTION

The present invention relates generally to electronic protection systemsand can be implemented within any appropriate navigation system thatrelies on spread spectrum navigation systems. For the purpose ofexample, the foregoing description is drawn specifically toimplementations of GNSS receivers, but it will be appreciated that theinvention is generally applicable to any navigation system. Thefundamental baseband digital signal processing component used in a GNSSreceiver is known as a correlation engine, or correlator. A correlationengine correlates digitized samples of a received GNSS signal output byan analog-to-digital converter (ADC) with locally generated replicas ofthe carrier and spreading code components of the signal being received.If the local replica is adequately aligned with the carrier and codecomponents of the received signal, a large correlation result isproduced. The signal can be processed according to parameters of thesignal derived from the aligned local replica, thereby providingobservability of the actual received GPS signal parameters whose powerlevel can be well below that of thermal noise. These received signalparameters represent the magnitude of the de-spread signal and phase ofits carrier with respect to the locally-generated carrier.

In accordance with an aspect of the present invention, apost-correlation characterization of emitters is added to a spatialfiltering process in order to identify threats that stay below the noisefloor, and thus cannot be detected at the pre-correlation stage, but canstill significantly degrade the tracking quality of GPS signals. Thesethreats can include spoofers and meaconers. The post-correlation stepfirst implements multi-directional beam-steering, with weights varied tosteer the array beam simultaneously in multiple directions while nullingout those jamming sources that are characterized by the signalcovariance matrix calculated at the pre-correlation step. If a signalenergy peak is found in any steering direction other than the directionof the satellite, an interfering signal coming from that direction isidentified. The procedure can be repeated for every value of the codephase from the open-loop search space to enable identification ofemitters whose code phase differ from the direct signal by more than acode chip. It will be appreciated that multi-directionalpost-correlation beam-steering can be implemented at the correlator ratewith weights applied in software to reduce the overall computationalload.

Accordingly, the proposed GNSS receiver combines postcorrelation andprecorrelation data to achieve a complete view of potential threats tothe integrity of the navigation system. Specifically, precorrelationestimation identifies the presence of jammers and includes estimation ofthe noise covariance matrix between individual antenna elements for thecomputation of digital beam-forming spatial weights. Post-correlationestimation is used to protect against emitters below the noise floorwhile mitigating broadband threats.

FIG. 1 illustrates a cascaded electronic protection (EP) system assembly10 for a global navigation satellite system (GNSS) in accordance with anaspect of the present invention. The received signals from the variouselements of the antenna are provided to a preprocessing engine 12 thatprepares digital representations of the received signals for furtherprocessing. For example, each signal can be downcoverted at an analogdownconverter to an intermediate frequency, and digitized into a streamof digital samples. These digitized input streams are then downconvertedto baseband as respective in-phase, i(t), and quadrature, q(t),components.

The baseband in-phase and quadrature components can be used to representa radio signal, s(t), as a complex vector (phasor) with real andimaginary parts. Two components are required so that both positive andnegative frequencies, relative to the channel center frequency, can berepresented:s(t)=x(t)+jy(t)  Eq. 1

For the stream of digital samples from each antenna element, thepreprocessing engine 12 first provides a temporal cancelation ofemitters at a bank of finite impulse response (FIR) filters 14 andsubjects each input stream to a correlation with a replica GNSS code ata correlation engine 16. Filter coefficients for the back of FIR filters14 are computed at a precorrelation characterization component 18 basedon covariance between signal samples on different filter taps. Temporalfiltering efficiently mitigates narrow-band jamming and can utilize anyone of several optimizations for computation of the filter coefficientssuch as an adaptive transversal filter or a least mean squaresminimuzation.

The illustrated EP assembly uses a cascaded approach that separatestemporal filtering and digital beam-forming operations. Accordingly,temporal filtering is carried out before the correlation process,whereas the digital beam-forming function is performed after thecorrelation. The cascaded implementation has a number of advantages suchas reduction in the execution rate of the digital beam-forming, whichresults in reduced computational load, as well as capability forpost-correlation characterization of RF environments, which enablesidentification of emitter signals that stay below the noise floor (suchas spoofing and meaconing) and cannot be observed at pre-correlation.

A precorrelation component to the spatial filtering can be determined ata spatial weight computation component 22, which utilizes data from theprecorrelation characterization component 18 to determine an optimal setof weights for digital beam-forming. For beam-forming, the complexbaseband signals are multiplied by the complex weights to apply thephase shift and amplitude scaling required for each antenna element.w _(k) =a _(k) e ^(j sin(θ) ^(k) ⁾  Eq. 2where w_(k) is the complex weight for a k^(th) antenna element, θ_(k) isthe phase shift of the weight, and a_(k) is an amplitude of the weight.

The specific beam-forming algorithm utilized with the spatial weightcomputation component 22 can utilize any one of a number of optimizationcriteria for the computation of spatial array weights such as minimumvariance (MV), minimum variance distortion-less response (MVDR), andadaptive filtering with bias constraints. Each of these algorithms forthe computation of digital beam-forming weights generally requirescharacterization of the emitter signal environment. In the illustratedimplementation, emitters are characterized by a multi-element signalcovariance matrix that is computed based on both pre-correlationcharacterization 18 and post-correlation characterization 24. Signalcovariance between different array elements can be computed based ondown-sampled GPS signal at the output of the FIR filter bank 14. Foremitter-free cases, this matrix has a diagonal form, but the presence ofemitters introduces off-diagonal terms which can be minimized byoptimization. Estimates of signal covariance are directly incorporatedinto the weight computation procedures for most optimization algorithms.

To provide the postcorrelation contribution to the weight computation,the temporally filtered outputs of the FIR filter bank 14 are fed intothe correlation engine 16, which wipes-off code and carrier signals (forcode and carrier parameters from a certain search space) and accumulatesthe results over a predetermined interval (e.g., one millisecond). Thecorrelation results are provided to a postcorrelation characterizationcomponent 24 where outputs of individual antenna elements are combinedfor digital beam-forming to enable spatial cancellation of emitters. Forexample, the array beam can be steered in multiple directions using onemillisecond correlation outputs. Local energy maxima in angulardirections other than the satellite's identify emitter signals, and thedigital beam-forming algorithms implemented at the spatial weightcomputation component 22 can be augmented by nulling constraints inorder to suppress the influence of these additionally observed sourcesof interference on the signal tracking quality.

Each of the determined weights and the correlation results are providedto a weighting and summation component 26 that provides a weightedlinear combination of the correlation results reflecting the determineddigital beam-forming weights. The results of this weighted linearcombination can then be provided to a navigation component (not shown)for further processing.

FIG. 2 illustrates one implementation of an electronic protection system50 in accordance with an aspect of the present invention. The receiver50 includes a multi-element antenna 52 that provides a plurality ofreceived signals to respective digital antenna electronics (DAE)assemblies 54-56. In one implementation, the antenna 52 has sevenelements, and produces a signal at each element. Each DAE assembly 54-56prepares digital representations of the received signals for furtherprocessing. For example, each DAE can downconvert its received analogsignal to an intermediate frequency, digitized the intermediatefrequency signal into a stream of digital samples, and downconvert thedigital signal to baseband.

The baseband digital samples are provided to a bank of temporal filters60-62 which provides a temporal cancelation of emitters, as to mitigatenarrow-band jamming. To this end, each input stream is provided to anassociated shift register 64-66 that applies a coarse delay to the inputstreams. Specifically, the shift registers 64-66 can delay theirrespective input streams by integer increments of samples. A fine delaycan be applied to each input stream at respective finite impulseprocessing elements (FIR-PE) 68-70. Temporal interference suppression isimplemented in a form of finite impulse response (FIR) filter withadaptively selected weights. For discrete time t_(n), the output of the(2N+1)-tap filter is defined as:x _(FIR)(n)=Σ_(k=−N) ^(N) a _(k) x(n+k)  Eq. 3

where x(n+k) is the signal samples at individual taps of the filter, anda_(k) is the filter weight.

The resulting delayed input streams are provided to each of a covarianceestimation component 72 and a correlation engine 74. The covarianceestimation component 72 calculates a signal covariance matrix based onGPS signal samples, and an autocorrelation vector is precalculated andstored. The weights for the FIR-PE filter bank 68-70 are selectedadaptively minimizing the filter output error via a technique such asthe least mean-squares (LMS) where the tap weight vector is computed tominimize the filter output error using the sample variance andautocorrelation. Since signal samples of different taps are processed byexactly the same RF chain, the autocorrelation function is computed byrepresenting the GPS signal as x[n]=PRN(n)·sin(2π·f_(IF)·t_(n)), wherePRN is a pseudorandom code and f_(IF) is an intermediate carrierfrequency after a down conversion at the DAE 54-56. The determinedweights can be provide to the FIR-PE filter bank 68-70, as well as aspatial weight computation element 76.

The correlation engine 74 compares each signal stream to a replica GNSScode, representing an expected pseudorandom code in the received signal,to determine an associated correlation result for each signal streamrepresenting its similarity to the replica code. The correlation resultsare provided to respective multipliers 80-82, as well as apostcorrelation weight component 84 that determines the locations ofemitters exhibiting interference below the noise floor (e.g., spoofersand meaconers). To this end, the postcorrelation weight component 84steers the array beam simultaneously in multiple directions to applygain toward multiple satellites. The directions of any located emittersare identified by detection of multiple correlation peaks whosedetection parameters are provided to the spatial weight computationelement 76.

The spatial weight computation element 76 implements a digitalbeam-forming function (DBF) by optimizing the adaptive criteria with anysupplied constraints for individual satellites, the location of which isprovided by from associated navigation data 86. For instance, if thebeam steering is optimized for all satellites in view, it significantlyreduces the number of spatial nulls that can be generated forinterference suppression: the total number of nulls is N−K where N isthe number of antenna elements and K is the number of satellites. If theDBF is performed to optimize the jamming suppression only (i.e., withoutconsidering satellite signals) it increases the null availability to N−1but can potentially degrade or cancel-out signal reception for somesatellites. Integration of DBF into the signal tracking processeliminates these disadvantages. Specifically, undisturbed signalreception in the satellite's direction can be used as an optimizationconstraint. Similarly, if the postcorrelation weight component 84 findsstrong emitter peaks, generation of spatial nulls in the emitter signaldirection can also be added as an optimization constraint to thecomputation of spatial weights.

The spatial weight computation element 76 calculates spatialbeam-forming weights in order to eliminate spatially-correlated jammingsignals. This can be accomplished via any of a number of optimizationalgorithms, subject to the additional constraints imposed by thenavigation data 86 and the postcorrelation weight component 84. Theseweights are provided as second inputs to the multipliers 80-82 and theoutputs of the multipliers are summed at a summation component 90 toprovide a final, spatially and temporally filtered correlation result.

It will be appreciated that, since the DBF is performed at thecorrelator level, carrier phase measurement fidelity is preserved.Specifically, since all phase manipulations are known to both the beamformer and receiver, it is possible to explicitly compensate for carrierphase biases that are due to spatial beam-forming. This compensation isperformed at a carrier phase repair component 92. It will beappreciated, however, that the phase repair can instead be performedimplicitly, for example, as optimization constraints during thebeam-forming process. The phase corrected sample can then be provided toan integrator 94, where correlation results are accumulated over anextended period for retrieval by an associated navigation system (notshown).

In view of the foregoing structural and functional features describedabove, a methodology in accordance with various aspects of the presentinvention will be better appreciated with reference to FIG. 3. While,for purposes of simplicity of explanation, the methodologies of FIG. 3is shown and described as executing serially, it is to be understood andappreciated that the present invention is not limited by the illustratedorder, as some aspects could, in accordance with the present invention,occur in different orders and/or concurrently with other aspects fromthat shown and described.

FIG. 3 illustrates a method 100 for adaptive electronic protection in anavigation system in accordance with an aspect of the present invention.At 102, temporal filtering is applied to each of a plurality of inputstreams to provide a plurality of filtered input streams. In oneimplementation, a coarse delay of an integer increment of samples at anassociated sampling rate is applied, and the delayed input stream isprovided to a finite impulse response (FIR) filter, having adaptivelyselected weights, to apply a fine delay to the input stream. At 104, acovariance matrix representing the plurality of filtered input streamsis generated. At 106, a plurality of correlation results are generated,with each correlation result representing one of the plurality offiltered input streams.

At 108, a beam-forming weight is calculated for each input stream fromthe covariance matrix and the plurality of correlation results. In oneimplementation, the beam-forming weight for each input steam iscalculated via an optimization process having at least one optimizationconstraint determined from the covariance matrix. The optimizationprocess can also include, for example, further constraints derived froman integrated navigation data representing the position of a set ofglobal navigation satellite system (GNSS) satellites as well locationsof one or more other emitters not affiliated with the set of GNSSsatellites, such as a spoofer or meaconer.

At 110, a spatially filtered correlation result is determined from theplurality of correlation results and the beam-forming weight for eachinput stream. For example, each correlation result can be multiplied byits associated weight, and the weighted correlation results can besummed to provide the spatially filtered correlation result. At 112, thespatially filtered correlation result is compensated for carrier phasebiases due to spatial beam-forming if not the carrier phase biascompensation is not performed implicitly via optimization constraints.Once the phase compensation is complete, the spatially filteredcorrelation result can be provided to an associated navigation systemfor further processing.

What have been described above are examples of the present invention. Itis, of course, not possible to describe every conceivable combination ofcomponents or methodologies for purposes of describing the presentinvention, but one of ordinary skill in the art will recognize that manyfurther combinations and permutations of the present invention arepossible. Accordingly, the present invention is intended to embrace allsuch alterations, modifications, and variations that fall within thescope of the appended claims.

What is claimed is:
 1. A method for adaptive processing in a navigationsystem comprising: applying, at a receiver, temporal filtering to eachof a plurality of input streams received at a plurality of antennas ofthe receiver to provide a plurality of filtered input streams;generating, at the receiver, a covariance matrix representing theplurality of received input streams; generating, at the receiver, aplurality of correlation results, each representing one of the pluralityof filtered input streams; and calculating, at the receiver, abeam-forming weight for each received input stream via an optimizationprocess that has at least one parameter determined based on thecovariance matrix and at least one constraint determined based on theplurality of correlation results, wherein the at least one parameterduring the optimization process provides a spatial null in a directionof an interfering signal above a noise floor and the at least oneconstraint during the optimization process provides a spatial null in adirection of another interfering signal below the noise floor.
 2. Themethod of claim 1, wherein applying temporal filtering to each of aplurality of received input streams comprises: applying, at thereceiver, a coarse delay to the received input stream comprising aninteger increment of samples at an associated sampling rate; andapplying, at the receiver, a finite impulse response (FIR) filter,having adaptively selected weights, to apply a fine delay to thereceived input stream.
 3. The method of claim 1, wherein calculating, atthe receiver, a beam-forming weight for each received input stream fromthe covariance matrix and the plurality of correlation results comprisescalculating the beam-forming weight for each received input steam via anoptimization process having at least one optimization constraintdetermined from the covariance matrix.
 4. The method of claim 3, theoptimization process comprising one of a minimum variance process, aminimum variance distortion-less response process, or adaptive filteringwith bias constraints.
 5. The method of claim 3, the optimizationprocess being constrained by each of navigation data representing theposition of a set of global navigation satellite system (GNSS)satellites and a location of an emitter that is not affiliated with theset of GNSS satellites.
 6. The method of claim 1, further comprising:determining, at the receiver, a spatially filtered correlation resultfrom the plurality of correlation results and the beam-forming weightfor each received input stream; and compensating, at the receiver, thespatially filtered correlation result for carrier phase biases due tospatial beam-forming.